DocumentCode
725866
Title
Mining Patterns of Unsatisfiable Constraints to Detect Infeasible Paths
Author
Sun Ding ; Hee Beng Kuan Tan ; Lwin Khin Shar
Author_Institution
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore
fYear
2015
fDate
23-24 May 2015
Firstpage
65
Lastpage
69
Abstract
Detection of infeasible paths is required in many areas including test coverage analysis, test case generation, security vulnerability analysis, etc. Existing approaches typically use static analysis coupled with symbolic evaluation, heuristics, or path-pattern analysis. This paper is related to these approaches but with a different objective. It is to analyze code of real systems to build patterns of unsatisfiable constraints in infeasible paths. The resulting patterns can be used to detect infeasible paths without the use of constraint solver and evaluation of function calls involved, thus improving scalability. The patterns can be built gradually. Evaluation of the proposed approach shows promising results.
Keywords
data mining; infeasible paths detection; pattern mining; unsatisfiable constraints; Accuracy; Pattern matching; Prototypes; Scalability; Software; Testing; Training; Infeasible paths; pattern mining; static analysis; structural testing; symbolic evaluation;
fLanguage
English
Publisher
ieee
Conference_Titel
Automation of Software Test (AST), 2015 IEEE/ACM 10th International Workshop on
Conference_Location
Florence
Type
conf
DOI
10.1109/AST.2015.21
Filename
7166270
Link To Document